Physics-informed neural networks (PINNs) have shown promising potential for solving partial differential equations (PDEs) by integrating physical laws into the training process. However, their application to multi-material neutron diffusion problems in nuclear reactor physics presents significant challenges due to discontinuities in material properties at interfaces, where abrupt changes in diffusion coefficients lead to non-smooth solutions that are difficult for neural networks to approximate accurately. To address these limitations, we propose an enhanced Physics-Specialized Neural Network (PSNN) approach, integrated with a Source Iteration (SI) technique. This method introduces improved construction methods for specialized functions, utilizing both low-order and high-order polynomial approaches, with specific implementations for one-dimensional and two-dimensional multi-material problems. The specialized functions are engineered to inherently satisfy value and flux continuity conditions at material interfaces as hard constraints, rather than as soft constraints incorporated into the loss function. The SI-PSNN method combines the interface handling capabilities of PSNN with the efficiency of source iteration for eigenvalue problems. We demonstrate the effectiveness of this approach through comprehensive numerical experiments. For multi-group eigenvalue problems, SI-PSNN achieves validation on classical reactor physics benchmarks, producing L-2 errors of 8.22x10(-4) and 1.34x10(-3) for two energy groups on the TWIGL benchmark, with a k(eff) error of only 10.20 pcm, significantly outperforming the SI-PINN, which records errors of 2.48 x 10-2 and 3.01 x 10-2 with a k(eff) error of 922.28 pcm. Additionally, high accuracy is maintained on the IAEA benchmark with 69 subdomains, yielding L-2 errors of 3.30 x 10(-3) and 3.10 x 10(-2), along with a k(eff) error of 124.54 pcm. The proposed method alleviates the limitations of PINNs in multi-material neutron diffusion problems, explores the application of PSNN in neutron diffusion eigenvalue problems, and enhances the capability of physics-informed neural networks in nuclear reactor physics calculations.

PURPOSE:Nuclear emergency medical rescue is a critical component of the nuclear emergency response system, playing a vital role in safeguarding public life and health. To address the urgent need for rapid, wide-range radiation biodosimetry in nuclear emergency scenarios, this study utilized female C57BL/6J mice model to develop a machine learning (ML) framework for radiation-responsive biomarker screening and dose reconstruction across a broad dose range (0-12 Gy), laying a foundational preclinical basis for future translational research in human biodosimetry. MATERIALS AND METHODS:The blood sample of mice was collected at 24 hours and seven days post-irradiation. The gene expression was evaluated by transcriptomic sequencing. Further, differential expression analysis, Spearman's correlation filtering and Boruta algorithm were sequentially employed for screening radiation biomarkers. The stacking model integrating multiple ML algorithm was established for dose reconstruction. The gene expression was ultimately validated by more practical qRT-PCR method. RESULTS:Spearman's correlation filtering and Boruta algorithm was employed to identify 172 highly robust biomarkers from an initial pool of 25,654 genes. By utilizing a stacked ensemble ML approach, high-accuracy dose reconstruction was achieved across a broad range of 0-12 Gy, with an R2 of 0.952 and an RMSE of 0.938 Gy, significantly outperforming conventional regression analysis and individual ML models. Further refinement reduced the gene panel to just 15 key markers while preserving reconstruction accuracy comparable to the full 172-gene model. Experimental validation via qRT-PCR confirmed the reliability of these biomarkers, demonstrating the framework's potential for translation into a field-deployable diagnostic platform for radiation exposure assessment. CONCLUSIONS:We established ML framework that incorporates a multi-stage biomarker screening strategy and a stacking ML mode, to achieve rapid and accurate dose reconstruction across a wide dose range. This methodology provides a novel technical solution for nuclear emergency medical response.

The 20-inch photomultiplier tubes (PMTs) used in the Jiangmen Underground Neutrino Observatory (JUNO) are a critical component of the experiment, enabling the detection of neutrinos through their interaction with 20 kilotons of liquid scintillator. The objective of this study was to determine the PMT timing parameters by analyzing the results from the JUNO PMT testing scanning station. The testing system was designed to illuminate the PMT with a stabilized LED, and the resulting PMT-generated signals were used to evaluate the PMT’s characteristics and performance. These signals included the main signal corresponding to the external source as well as random noise. The study focused on analyzing key PMT timing parameters, including rise time, fall time, full width at half maximum (FWHM), and relative transit time spread (TTS), which were directly derived from the PMT-generated signals. To reduce the random noise in the signals before calculating these parameters, two methods were employed: fast Fourier transform (FFT) with cutoff frequencies ranging from 0 to 500 MHz and moving average. The FFT was used to filter out high-frequency noise, while the moving average was applied to smooth the signal. Applying the FFT altered the PMT waveform and effectively removed some random noise, which also resulted in a reduction of the calculated timing parameters by less than 0.15 ns. However, setting a cutoff frequency above 150 MHz may not be ideal, as it could cause the reconstructed waveform to lose key characteristics during the process. On the other hand, applying a moving average with 5 points smooths the reconstructed waveform but also leads to its widening, which compromises the PMT’s key characteristics and increases the calculated timing parameters at least 0.3 ns. To conclude, using the FFT with a 150 MHz filter could be a more suitable option for reducing noise from the PMT signal while preserving its key characteristics. The moving average method with 5 points or more may not be as effective for PMT noise reduction, as it tends to lose efficiency in maintaining the essential features of the waveform. This study provides valuable insights into optimizing signal processing techniques for accurate PMT performance evaluation in large-scale neutrino experiments like JUNO.

The Jiangmen Underground Neutrino Observatory (JUNO) collaboration has completed the construction of the 20,000-ton liquid scintillator detector and the associated muon veto detector system. To meet the physics objectives, the materials used in the detector must exhibit low radioactive contamination. The single-event rate in the fiducial volume (R < 17.2 m) of the scintillator is required to be approximately 7 Hz for energies above 0.7 MeV, resulting in an accidental coincidence background of about 1 event per day for reactor neutrino physics analyses. Since the beginning of the construction phase, we have screened the natural radioactivity content of thousands of materials, to select those that meet the design background budget. The radioactive impurity concentrations of the materials ultimately used in the JUNO detector are summarized in this paper. The construction of the entire detector and the subsequent filling of the liquid scintillator were completed in August 2025. From the initial data, the total count rate of natural radioactivity within the detector's fiducial volume has met the requirements and is sufficient to support the reactor antineutrino analysis.

We present a data acquisition (DAQ) software based on the MIDAS framework, specifically for gaseous detectors to support the detector deployments and applications. It implements a comprehensive suite of functions, including parameter configuration, data acquisition, decoding, and storage, alongside web-based operation and real-time monitoring capabilities. We establish a fully unified workflow spanning data acquisition to offline analysis, enabling real-time visualization of signal waveforms and energy spectra. The system has been successfully deployed in the PandaX-III experiment, which utilized a high-pressure gaseous detector to search for neutrinoless double beta decay. Its performance and stability have been validated through tests involving two distinct electronics setups and joint commissioning with the detector.

A new multi-detector array named HALIMA (Hybrid Array for LIfetime MeAsurement) has been developed at Lanzhou for nuclear structure studies in fission. The array comprises eight BGO-shielded High-Purity Germanium detectors and twenty fast Ce-doped Lanthanum Bromide [LaBr _3 (Ce)] detectors shielded with CsI(Tl). HALIMA is further complemented by two ancillary detector systems: fission fragment (FF) detectors and β detectors. This configuration enables precise sub-nanosecond lifetime measurements using the fourfold FF/ β -Ge-LaBr _3 (Ce)-LaBr _3 (Ce) coincidence technique. The performance and specifications of the detectors, associated electronics, and the data acquisition system are presented in detail. The advantage of FF selectivity is emphasized, which significantly enhances sensitivity to specific fission channels. Using this approach, the lifetimes of the nuclear excited states populated in the spontaneous fission of ^252 Cf were measured, showing good agreement with the established literature values.

Conventional digital pulse processors (DPPs) for silicon drift detectors (SDDs) employ CR differentiation circuits for pulse signal extraction from transistor reset preamplifiers. The non-ideal characteristics of the coupling capacitor cause signal tailing distortion after trapezoidal shaping, exacerbating baseline drift and fluctuation, which leads to the degradation of energy resolution with increasing input count rate (ICR). To address this issue, this study developed a DPP using a time-variant baseline subtraction technique. With a digital-to-analog converter (DAC) that dynamically tracks the output of the charge-sensitive preamplifier, the incident particle pulse signals are extracted with a subtractor circuit, thereby eliminating the need for an AC coupling capacitor and the associated signal distortion. This article first introduces the characteristics of the SDD's output signal and the factors affecting energy resolution, and then reveals the signal distortion caused by the CR differentiator through practical measurement. Subsequently, the hardware design and the key algorithm implementation of the DPP were described in detail, followed by an experimental comparison with the CR differentiation, ramp subtraction, and direct sampling methods. Experimental results demonstrate that the developed DPP exhibits excellent energy resolution stability, maintaining a resolution of 126.7 +/- 0.3 eV for the 5.89 keV X-rays across the ICR range of 10-500 kcps at an operating temperature of -45 C-degrees . In contrast, the resolution of the CR differentiation method deteriorates significantly with ICR, increasing from 124.3 to 132.8 eV. The developed DPP can be applied to any type of radiation detectors employing transistor reset preamplifiers for pulse-height analysis.

The landmark detection of neutrinos from SN1987A marked the dawn of neutrino astrophysics. The neutrino burst provided essential insights into fundamental properties of neutrinos, and served as key probes of stellar evolution and supernova dynamics. The recent advancement in coherent elastic neutrino-nucleus scattering enables the detection of core-collapse supernova burst neutrinos using tonne-scale liquid xenon detectors originally designed for dark matter direct detection. Leveraging this capability, we developed and deployed an online supernova monitoring system for the PandaX-4T experiment. This system features a GPS module with millisecond-level timing precision, a low false-alarm rate, and high sensitivity to galactic core-collapse supernova explosion events. The methodology is robust, directly scalable, and planned for implementation in the next-generation PandaX-20T experiment.

The detection of space-based gravitational waves is one of the most cutting-edge topics in contemporary physics. Among the critical components of detection instruments, the test mass (TM) release mechanism plays a pivotal role. After the satellite enters orbit, this mechanism must release the TM into space with high positional accuracy and minimal residual velocity, allowing it to be subsequently captured by the electrode housing. To ensure precise release in a free-floating environment, a piezoelectric stack actuator is employed as the actuation module in the crucial TM release mechanism. However, the hysteresis behavior inherent to piezoelectric materials introduces nonlinearities into the release process, which adversely affect the accuracy and stability of the system. To address this issue, we propose an electro-mechanical Bouc-Wen model, a novel hysteresis modeling framework that explicitly incorporates voltage rate dynamics and mechanical acceleration coupling. This enhancement enables more accurate characterization of asymmetric hysteresis under dynamic operating conditions, overcoming the limitations of the classical Bouc-Wen model. Through dynamic modeling and experimental validation of the TM release mechanism, and with model parameters optimized using a quantum particle swarm optimization algorithm, the proposed approach achieves high fitting accuracy. Furthermore, a hysteresis compensation strategy based on PID control is implemented and validated on the optimized model, demonstrating that the proposed method effectively mitigates the adverse impact of hysteresis on system performance.

Scalar-mediated interactions may exist among neutrinos, dark matter particles, or between the two. Double β-decay experiments provide a powerful tool to probe such exotic interactions. Using ^{136}Xe double β-decay data from PandaX-4T, we perform the first direct spectral search in the energy range of 20 to 2800 keV, setting the most stringent limits to date on scalar-mediated neutrino self-interactions for mediator masses below 2  MeV/c^{2}. These results place significant constraints on models invoking such interactions to alleviate the Hubble tension. Assuming the same scalar also mediates dark matter self-interactions, constraints on the dark matter-scalar interactions can be placed in conjunction with cosmological constraints.

We report a precise measurement of Po-216 half-life using the PandaX-4T liquid-xenon time-projection chamber (TPC). Rn-220, emanating from a Th-228 calibration source, is injected to the detector and undergoes successive alpha decays, first to Po-216 and then to Pb-212. The PandaX-4T detector measures the five-dimensional (5D) information of each decay, including time, energy, and three-dimensional position. Therefore, we can identify the Rn-220 and Po-216 decay events and pair them exactly to extract the lifetime of each Po-216. With a large data set and high-precision Rn-220 - Po-216 pairing technique, we measure the Po-216 half-life to be 143.7 +/- 0.5 ms, which is the most precise result to date and agrees with previously published values. The leading precision of this measurement demonstrates the power of the 5D calorimeter and the potential of exact parent-daughter pairing in the xenon TPC.

The Jiangmen Underground Neutrino Observatory (JUNO) aims to determine the neutrino mass ordering. As a satellite experiment of JUNO, the Taishan Antineutrino Observatory (TAO) is designed to precisely measure the reactor antineutrino energy spectrum at a near site, providing essential reference data for JUNO. TAO represents a novel cryogenic liquid scintillator experiment, utilizing Silicon Photomultipliers (SiPMs) for photon detection and operating at -50 ^∘ C to suppress SiPM dark noise. A full-size prototype of the central detector of TAO (approximately 2 ^∘ C, and using the surface flux of ground cosmic muons in the warm-up phase of the detector. The detector simulation software of TAO was adapted to the configuration of the prototype and the Monte Carlo prediction shows good agreement with the Co-60 data. A mild variation of the detector response was observed after correcting the temperature effect of the SiPM performance with the cosmic muon data.

We present a detailed characterization of the thermal neutron sensitive transparent glass scintillator SG101, benchmarked against the conventional LiF ZnS(Ag)based scintillator EJ426. The detection efficiency, energy resolution, and pulse shape discrimination (PSD) performance ofSG101 were evaluated under AmBe neutron irradiation. When coupled with organic scintillators(EJ200 or EJ276),the SG101 EJ200 system achieves a figure of merit (FOM) of 3.81 for thermal neutron/gamma separation, while the SG101 EJ276 configuration resolves three distinct particle populations gamma rays, fast neutrons, and thermal neutrons with FOM values of 3.46 and2.21, respectively. Correlation analysis reveals that the number of fast thermal neutron coincidence events significantly exceeds the accidental background, and the count of gamma fast thermal neutron triple-coincidence events is also far higher than the expected accidental rate, confirming significant physical correlations for both event types within a 100 us time window. These results demonstrate that SG101 is a promising candidate for applications requiring high-efficiency thermal neutron detection and precise event tagging coupling with a scintillator with PSD approach

The RELICS (REactor neutrino LIquid xenon Coherent elastic Scattering) experiment employs a dual-phase liquid xenon time projection chamber to search for Coherent Elastic Neutrino-Nucleus Scattering (CEνNS) induced by reactor neutrinos. To detect these sub-keV nuclear recoils and minimize signal attenuation, it is critical to maintain a sufficiently low impurity concentration in the detector. This work presents a comprehensive purity evolution model developed to describe impurity migration inside the detector. Utilizing measured material outgassing rates as input parameters, the model incorporates non-uniform transport mechanisms of the impurities, including circulation, vaporization, and condensation. The model is validated using data from a dedicated prototype detector. Based on this validated model, projections for the purification performance of the upcoming RELICS-10 and RELICS-50 detectors are provided.

Time series anomaly detection (TSAD) is crucial for ensuring the reliability of safety-critical systems. While recent multi-view approaches combining time and frequency domains have advanced performance, they still face important representation and fusion bottlenecks. Specifically, conventional linear spectral mappings may introduce representation distortion when decoding complex non-linear frequency shifts. Furthermore, by restricting the feature space to purely numerical modalities, existing deterministic models lack the global operational semantics required to contextualize operational shifts. This semantic void can lead to inter-modal cognitive conflicts and overconfident misclassifications under noisy environments, whereas traditional probabilistic uncertainty estimation methods remain computationally expensive for real-time TSAD. To address these limitations, this paper proposes a Tri-modal Evidential Synergy Network (TES-Net). First, TES-Net leverages a multi-order Kolmogorov-Arnold network alongside large language model (LLM)-extracted global semantics to adaptively decode non-linear spectral fluctuations and bridge the heterogeneous semantic gap. Second, to resolve inter-modal conflicts efficiently, we design a Tri-modal Evidential Fusion module grounded in Dempster-Shafer evidence theory. This mechanism explicitly quantifies modality-level epistemic uncertainty via mass functions in a single deterministic forward pass, dynamically discounting corrupted modalities through expectation aggregation. Finally, a semantic-gated correlation mechanism employs the global textual prior to modulate local inter-variate physical topologies, differentiating genuine anomalies from benign operational transitions. Extensive experiments on benchmark datasets demonstrate that the proposed method achieves competitive performance compared with recent baselines.

The Jiangmen Underground Neutrino Observatory (JUNO) is a 20-kton liquid scintillator-based, low-radioactivity, multi-purpose neutrino detector located 693 meters (1800 m.w.e.) underground in the Guangdong province, China. To detect scintillation light produced in the target, the detector is equipped with 17,612 20-inch photomultipliers (PMTs), forming the Large PMT system (LPMT). In addition, 25,600 3-inch photomultipliers (the Small Photomultiplier System or SPMT) are deployed in the gaps between the LPMTs. This paper presents the design and performance of the underwater front-end electronics developed for the SPMT system. It details the individual electronics boards and their key components, the inter-board interfaces, the system-level design, and the firmware architecture that supports data acquisition and control. It also outlines mechanical and thermal integration, board validation procedures, and system performance metrics. The readout chain includes digitization of 128 PMT channels per unit, synchronized time-stamping, charge measurement, event packaging, and bandwidth management. Comprehensive validation confirms the system's readiness to meet JUNO's stringent physics goals. The underwater electronics achieve noise levels as low as 0.04 photoelectrons with minimal crosstalk (below 0.4

The Jiangmen Underground Neutrino Observatory (JUNO) is a 20-kiloton liquid scintillator neutrino detector, located 650 meters (1800 m.w.e.) underground in Jiangmen, Guangdong, China. JUNO is primarily designed for reactor neutrino measurements and has been taking data since 2025. With the largest mass of its kind and an excellent energy resolution, JUNO is a leading observatory for high-precision measurements of MeV neutrinos. The standard global trigger system serves as the primary trigger for JUNO. We present a newly developed multi-messenger trigger system that extends the capabilities of the global trigger by providing a lower energy threshold and an independent monitoring capability. During the 2025 operation, it achieved an effective energy threshold of approximately 110 +/- 10 keV, providing a lower threshold configuration suitable for low-energy event analysis. The system shows the potential to further reduce the threshold to well below 100 keV. Based on the multi-messenger trigger system, an astrophysical monitor has been developed to receive and process external alerts from other messengers, such as gravitational-wave observations. A Transient Neutrino Burst Monitor is integrated to detect short-time-scale neutrino burst events and enables real-time monitoring of transient astrophysical phenomena. The system is sensitive to neutrino bursts from core-collapse supernovae within a distance of about 250 kpc.

We report a new measurement of the solar proton–proton (pp) neutrino flux via neutrino–electron elastic scattering using the PandaX-4T Run 2 data set collected between 2024 and 2026, corresponding to an exposure of 1.9 tonne·yr. Before Run 2 data taking, the detector underwent a series of upgrades to improve its response and background conditions. Time variations of radioactive noble-gas impurities are constrained using the physics data themselves, complemented by measurements from the gas-assay system. The analysis introduced improvements in the data processing chain, detector response characterization, and background models. A blind spectral analysis was then performed on the electronic-recoil data across a wide energy range from 20 to 1000 keV. In combination with the Run 0 data published earlier, the fitted pp flux is (8.5 ± 3.5)× 10^10 cm^-2s^-1, consistent with the prediction of the Standard Solar Model. With a statistical significance of 2.2σ above background, this marks the first positive indication of solar pp neutrino–electron scattering below an electronic-recoil energy of 165 keV.

Abstract The RELICS (REactor neutrino LIquid xenon Coherent elastic Scattering) experiment aims to detect coherent elastic neutrino-nucleus scattering from reactor antineutrinos using a dual-phase xenon time projection chamber (TPC). To validate the detector concept and ensure technical reliability for the full-scale experiment, a dedicated prototype was designed, constructed, and operated. This work presents an overview of the design, construction, and operational performance of the prototype, with emphasis on its major subsystems, including the TPC, cryogenics and xenon purification systems, slow control, and data acquisition. During operation, the detector demonstrated the capability to achieve a sub-keV energy threshold required for the RELICS physics program, as reflected by a measured single electron gain of (34.30 ± 0.01 (stat.)) PE/e $$^-$$ - and the successful detection of $$\mathrm {0.27~keV}$$ 0.27 keV L-shell decay events from $$\mathrm {^{37}Ar}$$ 37 Ar . In addition, essential data analysis techniques and simulation frameworks were developed and validated, establishing the technical foundation for future RELICS operations. The successful construction and operation of this prototype confirm the feasibility of the core technologies and provide the experimental basis for the full-scale RELICS detector.